--- title: "Enhancing Insurance Data Analytics: 5 Key Steps by Pilotbird" description: Take your insurance data analytics capabilities to the next level and position your organization for success with Pilotbird Underwriting's expertise. image: https://www.pilotbird.com/hubfs/Early%20majority%20adapting%20to%20big%20data%20insurance%20underwriting-1.svg --- Insurance leaders on promises of emerging data [Listen to podcast](https://www.pilotbird.com/blog/soa-podcast-promises-and-risks-of-emerging-data-in-insurance) [![Pilotbird](https://www.pilotbird.com/hubfs/raw_assets/public/Pilotbird_January2022/images/Pilotbird_Logo_Dark.svg "Pilotbird")](https://www.pilotbird.com/) [![Pilotbird](https://www.pilotbird.com/hubfs/raw_assets/public/Pilotbird_January2022/images/Pilotbird_Logo_Light.svg "Pilotbird")](https://www.pilotbird.com/) - [Technology](https://www.pilotbird.com/technology) - [Insights](https://www.pilotbird.com/blog) - [Technology](https://www.pilotbird.com/technology) - [Insights](https://www.pilotbird.com/blog) [Contact Us](https://www.pilotbird.com/contactus) [Contact Us](https://www.pilotbird.com/contactus) ![](https://px.ads.linkedin.com/collect/?pid=2764348&fmt=gif) # Enhancing Insurance Data Analytics: 5 Key Steps by Pilotbird ![Early majority adapting to big data insurance underwriting-1](https://www.pilotbird.com/hubfs/Early%20majority%20adapting%20to%20big%20data%20insurance%20underwriting-1.svg "Early majority adapting to big data insurance underwriting-1") Underwriting 19 Sep 2022, 4 Min Read The life insurance industry has long struggled with challenging fundamentals. Intense competition erodes value across the board, and only a few industry leaders turn a profit. Compounding the industry's struggles, [reports](https://www.reuters.com/business/life-insurers-adapt-pandemic-risk-models-after-claims-jump-2022-01-13/) indicate that the global life insurance industry experienced an increase in reported claims to $5.5 billion during the first nine months of 2021 from $3.5 billion for the whole of 2020 due to the COVID-19 pandemic. In this turbulent environment, enhancing underwriting performance is one proven way to boost competitiveness. But how can insurers achieve this? The use of data analytics capabilities is becoming table stakes in life insurance underwriting. It gives life insurance carriers the opportunity to gain valuable intelligence and insights to streamline processes, optimize resources, and improve profitability. In fact, according to a [Willis Towers Watson study,](https://www.wtwco.com/en-US/Insights/2019/07/the-financial-rationale-for-predictive-analytics) life insurance carriers who leverage predictive analytics, experience a 60% increase in sales and a 67% reduction in expenses. In this post, we'll review key steps for implementing better insurance data analytics in life insurance underwriting. ## **How to Implement Better Insurance Data Analytics in Life Insurance Underwriting** More and more insurers are investing in data analytics solutions and understand that these solutions are key to surviving in the rapidly evolving environment. Even so, a [recent study](https://www.businesswire.com/news/home/20200701005334/en/Turning-Data-Into-Insights-With-Commercial-Analytics-Quantzig%E2%80%99s-Recent-Article-Reveals-Three-Best-Practices-for-Insurers) found 90% of insurance companies struggle to see a positive case of data analytics solutions. This is mostly due to the poor implementation of insurance data analytics [solutions](https://www.pilotbird.com/blog/predictive-analytics-insurance). Below is an outline of the steps that insurers can use to optimize data analytics in life insurance  underwriting: ### **1. Problem Framing and Identification of Business Goals** Data analytics in life insurance underwriting typically begins with an insurer focusing on solving a given problem, such as reducing fraudulent claims or improving customer recommendations. Identify the most promising insurance products, determine which products and riders should be in the scope of the analysis, and define the relevant hypothesis to be tested. Your focus should be on clarifying a specific goal using measurable outcomes. Insurers may collaborate with statisticians to establish the metrics for measuring success. It's also crucial to place the goals in a broader context. ### **2. Data Extraction, Cleaning, and Crunching** Data is usually collected and stored in multiple systems, which require expert knowledge to extract data from. Insurers should be able to identify the data that is relevant to the underwriting process. They should be able to determine what data sets are available and how this data can be used to improve predictions and address other business goals. Once data is extracted, it is transformed and combined into an integral analysis dataset for validation and modeling purposes. That said, the relevance, suitability, quality, and cleanliness of data must be considered. Understanding how and why data is collected can help carriers identify any problems in advance prior to feeding it into their data analytics model. ![two insurance professionals at monitor using data analytics](https://www.pilotbird.com/hs-fs/hubfs/iStock-1252396957.jpg?width=1411&name=iStock-1252396957.jpg) ### **3. Development of the Model** Consider how different data analysis models might yield the most valuable outcome, and then work backward to determine the most ideal way of organizing the raw data into an appropriate set of features for the model. Experiment with different algorithms, features, and processes that strike the right balance between accuracy, performance, and any other aspects like explainability. Life insurers can use a data wrangling tool to transform raw data into more conclusive data sets for calculating a prediction. Most insurers prefer using predictive and descriptive underwriting and pricing models since they are built using quantitative and qualitative knowledge that considers all the business domains relevant to the analytics use case. ### **4. Deploy the Model to Support and Automate Business Decisions** The newly developed data analytics model is then put into action to see if it can deliver results. Insurance data analytics insights are only valuable if they make a meaningful difference in the underwriting process. It should, for instance, be able to help insurers determine how risk-averse an insured is. This way, they'll be better placed in determining whether or not someone qualifies to take a life insurance cover and, if so, what premiums they should pay. ### **5. Monitoring the Model to Compare Its Performance to the Expected Results** Suppose the data science was well executed, the data analytics model should be able to meet the accuracy, performance, and other requirements when it is deployed with live data. Even so, performance can change over time. In some cases, especially when extracting information from social media, potential policyholders may subvert the accuracy of the data analytics model by deliberately divulging misleading information on their social media accounts. In other cases, the data analytics model helps insurers obtain useful insights that they can use to close the loop in product design in the following ways:  - Extra-premium loadings that don't offer a significant premium increase versus claims should undergo re-evaluation by the actuarial team. The premiums can be either increased or converted into an exclusion.  - Extra-premium loadings that generate more premiums compared to their relative claims can be kept as-is or reduced to improve the competitive edge.  - Exclusions that don't provide sufficient protection against claims can be scrapped in the underwriting process to reduce costs and improve operational speed.  That said, upon the deployment of the model, continuous monitoring is required to ascertain whether it's meeting performance expectations. The work isn't complete here, though, given that there may be a need to redefine the model to ensure it stays in line with the changing life insurance industry market dynamics. ## **How Insurance Data Analytics Is Used in the Life Insurance Industry** Insurance data analytics is an extension of the techniques that insurers have used for several years to calculate risks and set premiums for their insurance policies. The manual underwriting techniques that insurers relied on in the past years are expensive and time-consuming. Insurance data analytics tools used in life insurance streamline the underwriting process and improve risk assessment, which maximizes the profitability of the insurers. Besides that, it also improves their customer retention rates. For instance, using these tools together with genetic profiling can help life insurance companies distinguish risks related to unhealthy lifestyles from those associated with genetic factors that are beyond the policyholder's control and adjust the policy accordingly. If you are looking to improve your underwriting process, look no further than [Pilotbird's insurance data analytics solutions](https://www.pilotbird.com/pilotbird-lifestyle-risk-scoring). These solutions have features such as scoring for assessment of lifestyle risk, hit rate for confidence level, plus it's designed for efficient use by teams. [Contact us](https://www.pilotbird.com/contactus?hsLang=en) for a free demo of our insurance data analytics solutions.  REFERENCES Dekkers, J. & Choudhury, A. (n.d). Insurance analytics: Applying analytics in the underwriting process. Deloitte.[https://www2.deloitte.com/nl/nl/pages/financial-services/articles/applying-insurance-analytics-in-the-underwriting-process.html](https://www2.deloitte.com/nl/nl/pages/financial-services/articles/applying-insurance-analytics-in-the-underwriting-process.html) Maryville University. (n.d). Predictive Analytics in Insurance: Types, tools, and the future.[https://online.maryville.edu/blog/predictive-analytics-in-insurance/](https://online.maryville.edu/blog/predictive-analytics-in-insurance/) Willis Watson Towers Survey. (2019, July 8). The financial rationale for predictive analytics.[https://www.wtwco.com/en-US/Insights/2019/07/the-financial-rationale-for-predictive-analytics](https://www.wtwco.com/en-US/Insights/2019/07/the-financial-rationale-for-predictive-analytics) Diemer, S. (n.d). Stay on top of your performance with insurance analytics.[https://www.datapine.com/insurance-analytics](https://www.datapine.com/insurance-analytics) BusinessWire. (2020, July 1). Turning data into insights with commercial analytics.[https://www.businesswire.com/news/home/20200701005334/en/Turning-Data-Into-Insights-With-Commercial-Analytics-Quantzig%E2%80%99s-Recent-Article-Reveals-Three-Best-Practices-for-Insurers](https://www.businesswire.com/news/home/20200701005334/en/Turning-Data-Into-Insights-With-Commercial-Analytics-Quantzig%E2%80%99s-Recent-Article-Reveals-Three-Best-Practices-for-Insurers) Cohn, C. & Hussain, Z. (2022, January 13). Life insurers adapt pandemic risk models after claims jump.[https://www.reuters.com/business/life-insurers-adapt-pandemic-risk-models-after-claims-jump-2022-01-13/](https://www.reuters.com/business/life-insurers-adapt-pandemic-risk-models-after-claims-jump-2022-01-13/) Share on Twitter Share on LinkedIn ![Evgeny Aleksandrov](https://www.pilotbird.com/hubfs/797518957cd317d1263bb91542e8046e.png) **Evgeny Aleksandrov** is an industry thought leader in the insurance industry with numerous articles on technology, innovation, and financial services. ### Leave a Comment Your email address will not be published. Required fields are marked \* ##### Read next - ###### [![How Machine Learning Insurance Underwriting Can Reduce Industry Bias](https://www.pilotbird.com/hubfs/Company%20using%20machine%20learning%20insurance%20underwriting%20to%20process%20work%20faster.svg) Underwriting How Machine Learning Insurance Underwriting Can Reduce Industry Bias 26 Sep 2022 4 Min Read](https://www.pilotbird.com/blog/how-machine-learning-insurance-underwriting-can-reduce-industry-bias) - ###### [![How Automated Insurance Underwriting Can Save Small Businesses Money](https://www.pilotbird.com/hubfs/Small%20business-1.svg) Underwriting How Automated Insurance Underwriting Can Save Small Businesses Money 27 Jun 2022 4 Min Read](https://www.pilotbird.com/blog/how-automated-insurance-underwriting-services-save-small-businesses-money) - ###### [![FinTech Underwriting: Unveiling Lifestyle Insights](https://www.pilotbird.com/hubfs/lifestyle_insight_v2-2.svg) Underwriting FinTech Underwriting: Unveiling Lifestyle Insights 11 Dec 2020 2 Min Read](https://www.pilotbird.com/blog/lifestyle-insights-for-underwriting-in-fintech-and-insurtech) - ###### [![AI in Insurance: Empowering Actuaries and Underwriters](https://www.pilotbird.com/hubfs/Imported_Blog_Media/ai2-1.jpeg) Underwriting AI in Insurance: Empowering Actuaries and Underwriters 24 Dec 2021 4 Min Read](https://www.pilotbird.com/blog/machine-learning-insurance-underwriting) - ###### [![Big Data In Insurance Underwriting - 6 Ways Early Majority Benefits](https://www.pilotbird.com/hubfs/Pilotbird-Engage-1.svg) Underwriting Big Data In Insurance Underwriting - 6 Ways Early Majority Benefits 27 Jun 2022 5 Min Read](https://www.pilotbird.com/blog/6-ways-early-majority-benefits-from-big-data-in-insurance-underwriting) - ###### [Underwriting Utilizing Social Data in Insurance Underwriting 12 Jan 2022 5 Min Read](https://www.pilotbird.com/blog/life-insurance-underwriting) #### Other insights - [![How Machine Learning Insurance Underwriting Can Reduce Industry Bias](https://www.pilotbird.com/hubfs/Company%20using%20machine%20learning%20insurance%20underwriting%20to%20process%20work%20faster.svg)](https://www.pilotbird.com/blog/how-machine-learning-insurance-underwriting-can-reduce-industry-bias) Underwriting 26 Sep 2022 4 Min Read ##### [How Machine Learning Insurance Underwriting Can Reduce Industry Bias](https://www.pilotbird.com/blog/how-machine-learning-insurance-underwriting-can-reduce-industry-bias) Unleashing the Potential: Machine Learning Insurance Underwriting to Combat Industry Bias Artificial Intelligence (AI) has evolved and has become one of the ways organizations use to streamline their... [Read More »](https://www.pilotbird.com/blog/how-machine-learning-insurance-underwriting-can-reduce-industry-bias) - [![How Automated Insurance Underwriting Can Save Small Businesses Money](https://www.pilotbird.com/hubfs/Small%20business-1.svg)](https://www.pilotbird.com/blog/how-automated-insurance-underwriting-services-save-small-businesses-money) Underwriting 27 Jun 2022 4 Min Read ##### [How Automated Insurance Underwriting Can Save Small Businesses Money](https://www.pilotbird.com/blog/how-automated-insurance-underwriting-services-save-small-businesses-money) Insurance is an established and heavily regulated industry. Because of this, insurers have been slower to accept technological development (such as automated insurance underwriting) compared to other... [Read More »](https://www.pilotbird.com/blog/how-automated-insurance-underwriting-services-save-small-businesses-money) - [![FinTech Underwriting: Unveiling Lifestyle Insights](https://www.pilotbird.com/hubfs/lifestyle_insight_v2-2.svg)](https://www.pilotbird.com/blog/lifestyle-insights-for-underwriting-in-fintech-and-insurtech) Underwriting 11 Dec 2020 2 Min Read ##### [FinTech Underwriting: Unveiling Lifestyle Insights](https://www.pilotbird.com/blog/lifestyle-insights-for-underwriting-in-fintech-and-insurtech) Many assume Fintech is a recent development in the financial world. Believe it or not, modern FinTech was first introduced in the 1950s when the first credit cards came out and again in 1967 by... [Read More »](https://www.pilotbird.com/blog/lifestyle-insights-for-underwriting-in-fintech-and-insurtech) [![Pilotbird](https://www.pilotbird.com/hubfs/raw_assets/public/Pilotbird_January2022/images/Pilotbird_Logo_Light.svg "Pilotbird")](https://www.pilotbird.com/) - [Terms & Conditions](https://www.pilotbird.com/terms-conditions) - [Privacy Center](https://www.pilotbird.com/privacy-center) - [Security](https://www.pilotbird.com/security) - [Careers](https://www.pilotbird.com/careers) [![logo-24](https://www.pilotbird.com/hubfs/linkedin.svg "logo-24")](https://www.linkedin.com/company/pilotbird/) Quick Links - [Pilotbird Lifestyle Risk Scoring](https://www.pilotbird.com/pilotbird-lifestyle-risk-scoring) - [Pilotbird Fraud Monitoring](https://www.pilotbird.com/pilotbird-fraud-monitoring) - [Technology](https://www.pilotbird.com/technology) - [Blog](https://www.pilotbird.com/blog) - [Contact Us](https://www.pilotbird.com/contactus) ### Get our newsletter ![Arch grants](https://www.pilotbird.com/hs-fs/hubfs/raw_assets/public/Pilotbird_January2022/images/arch-grants-1.png?width=1085&name=arch-grants-1.png "Arch grants") ![aicpa logo](https://www.pilotbird.com/hubfs/aicpa%20logo.svg "aicpa logo") ```json { "@context" : "https://schema.org", "@type" : "BlogPosting", "author" : { "@type" : "Person", "name" : "Evgeny Aleksandrov", "url" : "https://www.pilotbird.com/blog/author/evgeny-aleksandrov" }, "dateModified" : "2023-07-30T14:14:10.660Z", "datePublished" : "2022-09-19T15:00:00.000Z", "headline" : "Enhancing Insurance Data Analytics: 5 Key Steps by Pilotbird", "image" : [ "https://www.pilotbird.com/hubfs/Early%20majority%20adapting%20to%20big%20data%20insurance%20underwriting-1.svg" ], "mainEntityOfPage" : { "@id" : "https://www.pilotbird.com/blog/implement-insurance-data-analytics", "@type" : "WebPage" }, "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://www.pilotbird.com/hubfs/Pilotbird_Logo_Dark.svg" }, "name" : "Pilotbird" } } ``` ```json { "@context" : "http://schema.org", "@type" : "BlogPosting", "author" : { "@type" : "Person", "name" : "Evgeny Aleksandrov" }, "dateModified" : "July 30, 2023, 2:14:10 PM", "datePublished" : "2022-09-19 15:00:00", "description" : "Take your insurance data analytics capabilities to the next level and position your organization for success with Pilotbird Underwriting's expertise.", "headline" : "Enhancing Insurance Data Analytics: 5 Key Steps by Pilotbird", "image" : { "@type" : "ImageObject", "url" : "https://9002617.fs1.hubspotusercontent-na1.net/hubfs/9002617/Early%20majority%20adapting%20to%20big%20data%20insurance%20underwriting-1.svg" }, "mainEntityOfPage" : { "@id" : "https://www.pilotbird.com/blog/implement-insurance-data-analytics", "@type" : "WebPage" }, "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://9002617.fs1.hubspotusercontent-na1.net/hubfs/9002617/Capa%202.png" }, "name" : "Pilotbird" } } ``` ```json { "@context" : "http://schema.org", "@type" : "Organization", "address" : { "@type" : "PostalAddress", "addressCountry" : "", "addressLocality" : "New York", "addressRegion" : "NY", "postalCode" : "", "streetAddress" : "247 W 46th St " }, "alternateName" : "Pilotbird", "areaServed" : { "@type" : "GeoCircle", "geoMidpoint" : { "@type" : "GeoCoordinates", "latitude" : "40.75996223497667", "longitude" : "-73.98761007334504" }, "geoRadius" : "150 km" }, "description" : "Pilotbird empowers Life & Health and P&C insurance teams to better score risk and detect ineligible claims by analyzing social data points", "email" : "info@pilotbird.com", "image" : "https://www.pilotbird.com/hubfs/raw_assets/public/Pilotbird_January2022/images/Pilotbird_Logo_Dark.svg", "logo" : "https://9002617.fs1.hubspotusercontent-na1.net/hubfs/9002617/Capa%202.png", "mainEntityOfPage" : { "@id" : "https://www.pilotbird.com/blog/implement-insurance-data-analytics", "@type" : "WebPage", "description" : "Take your insurance data analytics capabilities to the next level and position your organization for success with Pilotbird Underwriting's expertise." }, "naics" : "513210", "name" : "Pilotbird", "sameAs" : [ "https://www.linkedin.com/company/pilotbird/" ], "telephone" : "", "url" : "/" } ``` ```json { "@context" : "https://schema.org/", "@type" : "BreadcrumbList", "itemListElement" : [ { "@type" : "ListItem", "item" : "https://www.pilotbird.com/", "name" : "Home", "position" : 1 }, { "@type" : "ListItem", "item" : "https://www.pilotbird.com/pilotbird-lifestyle-risk-scoring", "name" : "Pilotbird Lifestyle Risk Scoring", "position" : 2 } ] } ``` ```json { "@context" : "https://schema.org", "@type" : "Organization", "alternateName" : "Kiwi Insurance Services, Inc", "logo" : "https://www.pilotbird.com/hubfs/raw_assets/public/Pilotbird_January2022/images/Pilotbird_Logo_Dark.svg", "name" : "Pilotbird", "sameAs" : "https://www.linkedin.com/company/pilotbird/", "url" : "https://www.pilotbird.com/" } ``` ```json { "@context" : "https://schema.org/", "@type" : "BreadcrumbList", "itemListElement" : [ { "@type" : "ListItem", "item" : "https://www.pilotbird.com/", "name" : "Home", "position" : 1 }, { "@type" : "ListItem", "item" : "https://www.pilotbird.com/pilotbird-lifestyle-risk-scoring", "name" : "Pilotbird Lifestyle Risk Scoring", "position" : 2 }, { "@type" : "ListItem", "item" : "https://www.pilotbird.com/pilotbird-engage", "name" : "Pilotbird Engage", "position" : 3 }, { "@type" : "ListItem", "item" : "https://www.pilotbird.com/pilotbird-fraud-monitoring", "name" : "Pilotbird Fraud Monitoring", "position" : 4 }, { "@type" : "ListItem", "item" : "https://www.pilotbird.com/technology", "name" : "Pilotbird Technology", "position" : 5 }, { "@type" : "ListItem", "item" : "https://www.pilotbird.com/blog", "name" : "Pilotbird Blog", "position" : 6 }, { "@type" : "ListItem", "item" : "https://www.pilotbird.com/contactus", "name" : "Pilotbird Contact Us", "position" : 7 } ] } ``` ```json { "@context" : "https://schema.org", "@type" : "BlogPosting", "author" : { "@type" : "Organization", "name" : "Mani Kaur" }, "datePublished" : "2021-01-07", "description" : "Robert Eaton from Society of Actuaries on the uses of lifestyle data points to improve insurance experience. Tune in for the latest views in using alternative data sets to improve underwriting accuracy and prequalify leads.", "headline" : "Our CEO on podcast with Society of Actuaries", "image" : "https://www.pilotbird.com/hs-fs/hubfs/ceo_podcast-300x139-1%20(1).png?width=300&name=ceo_podcast-300x139-1%20(1).png", "mainEntityOfPage" : { "@id" : "https://www.pilotbird.com/blog/our-ceo-on-podcast-with-society-of-actuaries", "@type" : "WebPage" }, "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://www.pilotbird.com/hubfs/raw_assets/public/Pilotbird_January2022/images/Pilotbird_Logo_Dark.svg" }, "name" : "Pilotbird" } } ``` ```json { "@context" : "https://schema.org", "@type" : "BlogPosting", "author" : { "@type" : "Organization", "name" : "Mani Kaur" }, "datePublished" : "2022-01-11", "description" : "Insurance technology trends will increase competition with new entrants joining the market as existing players grapple with the hostile environment. McKinsey & Company agrees with these sentiments, affirming that technology will alter the structure of many organizations (1) in the coming decade. Future leaders in the industry will be organizations that integrate these technologies into their core processes and adopt an innovative mindset in light of the new realities.", "headline" : "5 Growing Insurance Technology Trends You Can’t Afford to Ignore", "image" : "https://www.pilotbird.com/hs-fs/hubfs/insurance-technology-trends.jpg?width=1420&name=insurance-technology-trends.jpg", "mainEntityOfPage" : { "@id" : "https://www.pilotbird.com/blog/insurance-technology-trends", "@type" : "WebPage" }, "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://www.pilotbird.com/hubfs/raw_assets/public/Pilotbird_January2022/images/Pilotbird_Logo_Dark.svg" }, "name" : "Pilotbird" } } ``` ```json { "@context" : "https://schema.org", "@type" : "BlogPosting", "author" : { "@type" : "Organization", "name" : "Mani Kaur" }, "datePublished" : "2022-09-05", "description" : "Social media and insurance records have enormous amounts of data on individuals. However, the below factors are the most consequential for health.", "headline" : "Social Media and Insurance: How BMI Is Reflected in Social Data", "image" : "https://www.pilotbird.com/hs-fs/hubfs/consumers%20providing%20information%20to%20social%20media%20and%20insurance%20companies.jpg?width=1420&name=consumers%20providing%20information%20to%20social%20media%20and%20insurance%20companies.jpg", "mainEntityOfPage" : { "@id" : "https://www.pilotbird.com/blog/social-media-insurance-how-bmi-is-reflected-social-data", "@type" : "WebPage" }, "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://www.pilotbird.com/hubfs/raw_assets/public/Pilotbird_January2022/images/Pilotbird_Logo_Dark.svg" }, "name" : "Pilotbird" } } ``` ```json { "@context" : "https://schema.org", "@type" : "BlogPosting", "author" : { "@type" : "Organization", "name" : "Mani Kaur" }, "dateModified" : "2022-10-10", "datePublished" : "2020-12-11", "description" : "The insurance industry is quickly following suit with multiple applications designed to improve the accuracy of underwriting. InsurTech disrupts the insurance landscape by improving customer experience, triaging customer to a product, and assessing underwriting risk. Let’s look at how these applications utilize lifestyle insights and social data points during the underwriting process.", "headline" : "Lifestyle Insights for Underwriting in FinTech and InsurTech", "image" : "https://www.pilotbird.com/hubfs/lifestyle_insight_v2-1.svg", "mainEntityOfPage" : { "@id" : "https://www.pilotbird.com/blog/lifestyle-insights-for-underwriting-in-fintech-and-insurtech", "@type" : "WebPage" }, "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://www.pilotbird.com/hubfs/raw_assets/public/Pilotbird_January2022/images/Pilotbird_Logo_Dark.svg" }, "name" : "Pilotbird" } } ```